Ponencia
Detection of microcalcifications in mammograms using 2D prediction filtering and a new statistical measure of the right tail weight
Autor/es | Acha Piñero, Begoña
Serrano Gotarredona, María del Carmen Rangayyan, Rangaraj M. |
Departamento | Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones |
Fecha de publicación | 2005-11 |
Fecha de depósito | 2022-06-06 |
Publicado en |
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ISBN/ISSN | 1727-1983 |
Resumen | In this paper, a new method to detect
microcalcifications in mammograms is presented.
The method is based on a candidate selection
procedure which consists of a two-dimensional linear
prediction adaptive filtering ... In this paper, a new method to detect microcalcifications in mammograms is presented. The method is based on a candidate selection procedure which consists of a two-dimensional linear prediction adaptive filtering followed by a statistical parameter calculation developed by the authors and called tail ratio (TR). The parameter TR characterizes the presence of microcalcifications in a ROI, and is extracted from the local probability distribution within a small region surrounding each candidate. Afterward a group of new and previously published features are used to feed a neural network that classifies the candidates into microcalcification or non-microcalcification. The algorithm has been tested with 38 digitized mammograms obtaining a sensitivity of 0.93 for a positive predictive value of 0.88. |
Cita | Acha Piñero, B., Serrano Gotarredona, C. y Rangayyan, R.M. (2005). Detection of microcalcifications in mammograms using 2D prediction filtering and a new statistical measure of the right tail weight. En The 3rd European Medical and Biological Engineering Conference, EMBEC 2005, Praga (República Checa). |
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